CN110544246A - automatic testing method and device and storage medium - Google Patents
automatic testing method and device and storage medium Download PDFInfo
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- CN110544246A CN110544246A CN201910824951.3A CN201910824951A CN110544246A CN 110544246 A CN110544246 A CN 110544246A CN 201910824951 A CN201910824951 A CN 201910824951A CN 110544246 A CN110544246 A CN 110544246A
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
- G06T7/0006—Industrial image inspection using a design-rule based approach
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- G06T2207/10—Image acquisition modality
- G06T2207/10004—Still image; Photographic image
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20081—Training; Learning
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V2201/00—Indexing scheme relating to image or video recognition or understanding
- G06V2201/02—Recognising information on displays, dials, clocks
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V30/00—Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
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Abstract
The invention provides an automatic test method, an automatic test device and a storage medium, wherein the method comprises the following steps: acquiring a vehicle instrument screenshot, and extracting pictures corresponding to different instrument function modules in the instrument screenshot; reading instrument data of pictures corresponding to the different instrument function modules through an ORC model and a classification model, and judging the character types of the instrument data; and comparing the character data with the requirement document, and adding the comparison result into the test case document. The problem that the traditional instrument testing method is low in efficiency is solved through the scheme, automatic testing of various instruments is achieved, and the efficiency of instrument testing is improved.
Description
Technical Field
the invention relates to the technical field of computers, in particular to an automatic testing method, an automatic testing device and a storage medium.
background
whether the automobile leaves a factory or is used, the instrument needs to be tested frequently, and the accuracy of automobile instrument display data is ensured. With the development of modern industrial technology, the number of automobile electronic control units is increased, the display data of vehicle instruments is increased, the traditional manual checking efficiency is low, and the modern testing requirements are difficult to meet.
at present, vehicle instrument data can be read by means of computer vision, but because the instrument types are different, only preliminary data extraction can be carried out, the actual data comparison and confirmation process is complex, a large amount of manpower and material resources can still be consumed, and the data testing efficiency is low.
Disclosure of Invention
in view of this, embodiments of the present invention provide an automatic testing method, an automatic testing device, and a storage medium, so as to solve the problem of low data testing efficiency of a vehicle instrument.
in a first aspect of embodiments of the present invention, there is provided a method, comprising:
acquiring a vehicle instrument screenshot, and extracting pictures corresponding to different instrument function modules in the instrument screenshot;
Reading instrument data of pictures corresponding to the different instrument function modules through an ORC model and a classification model, and judging the character types of the instrument data;
and comparing the character data with the requirement document, and adding the comparison result into the test case document.
In a second aspect of the embodiments of the present invention, there is provided an automated testing apparatus, including:
the extraction module is used for acquiring a vehicle instrument screenshot and extracting pictures corresponding to different instrument function modules in the instrument screenshot;
the reading module is used for reading the instrument data of the pictures corresponding to the different instrument function modules through an ORC model and a classification model and judging the character types of the instrument data;
And the comparison module is used for comparing the character data with the requirement document and adding the comparison result into the test case document.
in a third aspect of the embodiments of the present invention, there is provided an apparatus, including a memory, a processor, and a computer program stored in the memory and executable by the processor, where the processor executes the computer program to implement the steps of the method according to the first aspect of the embodiments of the present invention.
in a fourth aspect of the embodiments of the present invention, a computer-readable storage medium is provided, which stores a computer program, which when executed by a processor implements the steps of the method provided by the first aspect of the embodiments of the present invention.
In the embodiment of the invention, the instrument screenshot is obtained, the pictures corresponding to different instrument function modules in the instrument screenshot are extracted, the instrument data are read and classified through the trained ORC model and classification model, the classified instrument data are compared with the expected requirement document, and the test case result is obtained, so that the automatic test of the automobile instrument is realized, the problem of low test efficiency of the traditional instrument is solved, the test efficiency can be effectively improved, the labor and material cost is reduced, the reliability of the test result can be ensured based on the Autotest framework and the training model, and the practicability is high.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of an automated testing method according to an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of an automated testing apparatus according to an embodiment of the present invention;
Detailed Description
in order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the embodiments described below are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The first embodiment is as follows:
Referring to fig. 1, a flow chart of an automated testing method according to an embodiment of the present invention is schematically illustrated, including:
S101, obtaining a vehicle instrument screenshot, and extracting pictures corresponding to different instrument function modules in the instrument screenshot;
The vehicle meter screenshot is a screenshot of all meter function modules or part of the meter function modules of a vehicle, the screenshot is generally captured by a camera, and for the test of the meters, the type and the number of the meters contained in each screenshot should be consistent. The functional module of the instrument refers to the functional unit of the constituent instrument, and the prominent feature of the modern instrument is the functional modularization, i.e. several functional modules are combined on the basis of a customized PCB (printed circuit board) to facilitate data display. In different instrument function modules, including instruments such as speed per hour, rotational speed, water temperature, fuel and indicator lamps, the modes of displaying data types have differences, and corresponding pictures of different instrument function modules can be extracted and respectively identified.
preferably, a test case is created based on AutoTest, the test case comprising at least a function name, a confirmation point, a precondition, an operation step, and an expected result, wherein,
Function name (name): writing the functional point to be confirmed in the module,
confirmation point (summary): the function point is subdivided into the confirmation points,
Preconditions (preconditions): the preconditions for the execution of the use case,
Procedure (steps): the steps of the use case operation are described,
expected results (expectedresults): expected results after executing the use case.
writing a case corresponding message, and setting case judgment conditions after ensuring that case numbers correspond to each other, wherein the judgment conditions comprise time judgment and data type judgment, the time judgment refers to the time for sending a CAN signal to intercept an instrument image, and the data type judgment refers to the data type corresponding to the instrument, such as pictures corresponding to an indicator light and dial pointer corresponding to a vehicle speed.
Optionally, according to different display data of each instrument functional module in the instrument, pictures corresponding to different instrument functional modules are divided into different case types of a picture type, a character string type, a dial numerical value type, a progress bar type and a color type. Pictures such as indicator lights, alarm icons, module logos, etc., strings such as "close" characters, which are generally classified into white font strings and black font strings, and dial values such as vehicle speed or mileage pointers.
optionally, each meter screenshot case is subjected to module division, different meter data of the same module are numbered, and each meter picture in the screenshot is positioned according to the number so as to intercept the corresponding pictures of different meter function modules. The numbers of different modules are independent, the display position number of the content contained in the same module corresponds to the picture data, and the corresponding relation between the picture data and the instrument picture number can be corrected after the instrument picture coordinate is determined.
In the process of creating the test case based on the AutoTest, expected data is required to be filled, and the expected data generally corresponds to the content of a required document, namely the content of the meter pre-display data. Filling in the desired value varies in the filling content and form depending on the type of meter data.
S102, reading instrument data of pictures corresponding to different instrument function modules through an ORC model and a classification model, and judging the types of the instrument data;
The ORC (Optical Character Recognition) model can detect characters on paper or pictures through sample training, and generally recognizes Character data based on contrast and shape thereof. The classification model is a deep learning-based model, can distinguish specific prompt signs in the pictures according to the definition and the color brightness of the pictures, and is used for distinguishing indicator lights, alarm prompts, module signs and the like of the pictures in the embodiment. The classification model also comprises a color classification model used for font color or instrument prompt color.
The type of the meter data, namely the type of the meter display data, can be represented by different types such as numerical values, indicator lights and the like according to different functions of the meter.
specifically, the ORC model and the classification model are trained respectively, character string data are recognized through the ORC model, instrument data of a non-character string type are recognized through the classification model, the classification model comprises a color classification model, and the color classification model is used for recognizing indicator light data.
Illustratively, the meter data is identified based on the AutoTest Training tool, using OCR Training, Classification Training and Color Classification Training tool models, respectively.
For the OCR Training tool, it can be used to identify character-like data, including black font strings and white font strings. For the Classification Training tool, Training can be carried out through an OCR Training Interface tool, a word stock is generated, and the word stock is used for classifying the photo instrument data according to the image definition and the color brightness, and comprises the photo instrument data such as an indicator light, a warning mark and the like. For the Color Classification Training Interface tool, Training can be performed through an OCR Training Interface tool, a word stock is generated, and identification and judgment are performed on instrument data corresponding to the pure Color picture.
S103, comparing the character data with the requirement document, and adding the comparison result into the test case document.
the requirement document comprises an expected picture, an expected character string, an expected numerical value, an expected progress bar and an expected color. The picture has corresponding storage path, character string and numerical value and corresponding character data.
The test case document is an instrument data test structure, generally has test results of test cases with a plurality of instrument screenshots, obtains the test results of the instrument under different conditions according to the test case document, and can adjust and correct the problem of the instrument.
Compared with the problem of low efficiency of the traditional direct extraction test method, the method provided by the embodiment can effectively improve the test efficiency of the automobile instrument, and can identify and test multiple types of instrument data.
it should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, but should not constitute any limitation to the implementation process of the embodiments of the present invention,
Example two:
fig. 2 is a schematic structural diagram of an automated testing apparatus according to a second embodiment of the present invention, including:
the extraction module 210 is configured to obtain a vehicle meter screenshot, and extract pictures corresponding to different meter function modules in the vehicle meter screenshot;
Optionally, the obtaining a vehicle meter screenshot, and extracting pictures corresponding to different meter function modules in the vehicle meter screenshot includes:
And creating a test case based on the AutoTest, wherein the test case at least comprises confirmation content, a trigger condition, a judgment condition and an expected requirement.
Optionally, the obtaining a vehicle meter screenshot, and extracting pictures corresponding to different meter function modules in the vehicle meter screenshot further includes:
And dividing pictures corresponding to different instrument functional modules into different case types of pictures, character strings, dial numerical values, progress bars and colors according to different display data of each instrument in the instrument.
Optionally, the obtaining a vehicle meter screenshot, and extracting pictures corresponding to different meter function modules in the vehicle meter screenshot includes:
And carrying out module division on each meter screenshot case, numbering different meter data of the same module, and positioning each meter picture in the meter screenshot according to the numbering so as to intercept the pictures corresponding to different meter function modules.
the reading module 220 is configured to read instrument data of pictures corresponding to the different instrument function modules through an ORC model and a classification model, and determine character types of the instrument data;
optionally, the reading of the instrument data of the pictures corresponding to the different instrument function modules through the ORC model and the classification model specifically includes:
Respectively training the ORC model and the classification model, identifying character string data through the ORC model, and identifying instrument data of non-character string types through the classification model, wherein the classification model comprises a color classification model, and the color classification model is used for identifying indicator light data.
The comparison module 230 is configured to compare the character data with the requirement document, and add the comparison result to the test case document.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
It will be understood by those skilled in the art that all or part of the steps in the method for implementing the above embodiments may be implemented by a program to instruct associated hardware, where the program may be stored in a computer-readable storage medium, and when the program is executed, the program includes steps S101 to S103, where the storage medium includes, for example: ROM/RAM, magnetic disk, optical disk, etc.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. an automated testing method, comprising:
Acquiring a vehicle instrument screenshot, and extracting pictures corresponding to different instrument function modules in the instrument screenshot;
reading instrument data of pictures corresponding to the different instrument function modules through an ORC model and a classification model, and judging the character types of the instrument data;
And comparing the character data with the requirement document, and adding the comparison result into the test case document.
2. The method of claim 1, wherein the obtaining a vehicle meter screenshot, and the extracting pictures corresponding to different meter function modules in the meter screenshot comprises:
And creating a test case based on the AutoTest, wherein the test case at least comprises confirmation content, a trigger condition, a judgment condition and an expected requirement.
3. the method according to claim 1 or 2, wherein the obtaining a vehicle meter screenshot, and extracting pictures corresponding to different meter function modules in the meter screenshot further comprises:
and dividing pictures corresponding to different instrument function modules into different case types of pictures, character strings, dial numerical values, progress bars and colors according to different display data of the instrument function modules in the instrument.
4. the method of claim 1, wherein the obtaining a vehicle meter screenshot, and the extracting pictures corresponding to different meter function modules in the meter screenshot comprises:
And carrying out module division on each meter screenshot case, numbering different meter data of the same module, and positioning each meter function module picture in the meter screenshot according to the numbering so as to intercept the corresponding pictures of different meter function modules.
5. The method according to claim 1, wherein the reading of the meter data of the pictures corresponding to the different meter function modules through the ORC model and the classification model specifically includes:
Respectively training the ORC model and the classification model, identifying character string data through the ORC model, and identifying instrument data of non-character string types through the classification model, wherein the classification model comprises a color classification model, and the color classification model is used for identifying indicator light data.
6. An automated testing apparatus, comprising:
the extraction module is used for acquiring a vehicle instrument screenshot and extracting pictures corresponding to different instrument function modules in the instrument screenshot;
the reading module is used for reading the instrument data of the pictures corresponding to the different instrument function modules through an ORC model and a classification model and judging the character types of the instrument data;
And the comparison module is used for comparing the character data with the requirement document and adding the comparison result into the test case document.
7. the apparatus of claim 6, wherein the obtaining of the vehicle meter screenshot, and the extracting of the corresponding pictures of the different meter function modules in the meter screenshot comprises:
and creating a test case based on the AutoTest, wherein the test case at least comprises confirmation content, a trigger condition, a judgment condition and an expected requirement.
8. The apparatus of claim 6 or 7, wherein the obtaining a vehicle meter screenshot, and extracting pictures corresponding to different meter function modules in the meter screenshot further comprises:
And dividing pictures corresponding to different instrument function modules into different case types of pictures, character strings, dial numerical values, progress bars and colors according to different display data of the instrument function modules in the instrument.
9. An apparatus further comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the steps of the automated testing method according to any one of claims 1 to 5 are implemented when the computer program is executed by the processor.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the automated testing method according to any one of claims 1 to 5.
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Cited By (4)
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| CN111078565A (en) * | 2019-12-19 | 2020-04-28 | 上海轻维软件有限公司 | Analysis method of software test result based on HOG feature extraction and SVM multi-classifier |
| CN112765018A (en) * | 2021-01-12 | 2021-05-07 | 武汉光庭信息技术股份有限公司 | Instrument and meter debugging system and method |
| CN113138736A (en) * | 2020-01-16 | 2021-07-20 | 格莱菲卡公司 | Vehicle digital instrument display method and digital instrument display device using the same |
| CN113805834A (en) * | 2021-08-23 | 2021-12-17 | 桂林未来鹏创软件有限公司 | Automobile intelligent cabin testing method, system, device and storage medium |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111078565A (en) * | 2019-12-19 | 2020-04-28 | 上海轻维软件有限公司 | Analysis method of software test result based on HOG feature extraction and SVM multi-classifier |
| CN113138736A (en) * | 2020-01-16 | 2021-07-20 | 格莱菲卡公司 | Vehicle digital instrument display method and digital instrument display device using the same |
| CN112765018A (en) * | 2021-01-12 | 2021-05-07 | 武汉光庭信息技术股份有限公司 | Instrument and meter debugging system and method |
| CN112765018B (en) * | 2021-01-12 | 2022-09-13 | 武汉光庭信息技术股份有限公司 | Instrument and meter debugging system and method |
| CN113805834A (en) * | 2021-08-23 | 2021-12-17 | 桂林未来鹏创软件有限公司 | Automobile intelligent cabin testing method, system, device and storage medium |
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Application publication date: 20191206 |